Deep Learning-Assisted Nanoplasmonic Digital Immunoassay for Cytokine Profiling in Immune-Suppressed Patients using Designed Peptide Aptamers

Cytokine profiling in immune-suppressed patients plays a critical role in understanding their immune status and evaluating the effectiveness of immunomodulatory therapies. However, current immunoassay technologies face challenges in achieving rapid and accurate detection of multiple cytokines over a wide dynamic range. In this study, we propose a novel approach that combines deep learning with a nanoplasmonic digital immunoassay using rationally designed peptide aptamers as probes.<br/>The immunoassay system exhibits three notable features: (i) a simplified high-throughput biosensing chip fabrication process, (ii) an ultrasensitive nanoplasmonic digital imaging technique employing 50nm gold nanocubes (AuNCs) conjugated with antibody-mimicking peptide aptamers as detection probes, and (iii) a rapid and precise deep learning-based image processing method for digital signal analysis.<br/>By utilizing our developed immunoassay, we successfully achieved cytokine profiling with a wide working range of 0.1-10,000 picograms per milliliter (pg/ml) and exceptional detection limits in the femtogram range. This level of sensitivity enables the accurate detection of even trace amounts of cytokines, critical for monitoring immune-suppressed patients.<br/>Our findings demonstrate that this deep learning-assisted nanoplasmonic digital immunoassay, utilizing designed peptide aptamers, holds great potential for precise cytokine profiling in immune-suppressed patients. This innovative approach may contribute to improved clinical outcomes and informed treatment decisions for individuals with rapidly inflammatory disorders and immune suppression.